We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Generative topic models such as LDA are limited by their inability to utilize nontrivial input features to enhance their performance, and many topic models assume that topic assig...
Data cube computation and representation are prohibitively expensive in terms of time and space. Prior work has focused on either reducing the computation time or condensing the r...
Ying Feng, Divyakant Agrawal, Amr El Abbadi, Ahmed...
Use of model-checking approaches for test generation from requirement models have been proposed by several researchers. These approaches leverage the witness (or counter-example) ...
Mats Per Erik Heimdahl, Sanjai Rayadurgam, Willem ...